How to Use the AssemblyAI MCP in CrewAI

Q: How do I restrict which AssemblyAI tools an agent can use in CrewAI?

Import MCPServerHTTP and apply a toolfilter. This lets you give the summary tools to a writer agent while hiding the deletion tools.

Deploy autonomous CrewAI agents that transcribe, analyze, and summarize audio using AssemblyAI.

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Connect AssemblyAI MCP to CrewAI

Create your Vinkius account to connect AssemblyAI to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AssemblyAI with CrewAI

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Assign audio tasks via the CrewAI MCP Server

Give the `transcribe_audio_url` tool to a specialized researcher agent. This agent monitors a queue, grabs new media files, and initiates the processing job independently. A separate analyst agent takes over once the text is ready. It calls `get_speakers` to map out who dominated the conversation and pushes that report to shared memory.

Chain analytical tools across multiple agents

One agent runs `get_summary` to create an executive brief of a town hall meeting. Another agent simultaneously runs `get_topics` to tag the discussion points for the corporate wiki. CrewAI handles the coordination between these distinct tasks. The agents pass the transcript IDs back and forth without you writing any custom glue code.

Clean up processed files autonomously

Configure a janitor agent with access to `list_transcripts` and `delete_transcript`. It checks the workspace memory for completed jobs and removes the remote files. You restrict tool access using the `tool_filter` parameter in MCPServerHTTP. The cleanup agent only sees the deletion tools, preventing it from accidentally starting new transcription jobs.

Setup guide

Set up AssemblyAI MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke AssemblyAI tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="AssemblyAI Analyst",
    goal="Access and analyze AssemblyAI data via MCP.",
    backstory="Expert analyst with direct AssemblyAI access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent AssemblyAI transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="AssemblyAI Analyst",
        goal="Access and analyze AssemblyAI data via MCP.",
        backstory="Expert analyst with direct AssemblyAI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent AssemblyAI transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AssemblyAI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AssemblyAI MCP in CrewAI

Pass the Vinkius endpoint directly into the mcps array on your Agent definition. The framework automatically parses and registers the available audio tools.

Yes. You assign the same MCP endpoint to different agents. They share context through CrewAI memory while executing distinct transcription or sentiment tasks.

Import MCPServerHTTP and apply a tool_filter. This lets you give the summary tools to a writer agent while hiding the deletion tools.

The current tools require an audio URL. Your agents need to upload local files to a storage bucket first before calling the transcription endpoints.

All communication routes through an ephemeral V8 isolate. Vinkius processes the transcript text and speaker labels in memory, destroying the environment when the CrewAI session ends.

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